Mem AI (Knowledge Workspace) MCP Server for AutoGen 12 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Mem AI (Knowledge Workspace) as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="mem_ai_knowledge_workspace_agent",
tools=tools,
system_message=(
"You help users with Mem AI (Knowledge Workspace). "
"12 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Mem AI (Knowledge Workspace) MCP Server
Connect your Mem.ai workspace to any AI agent and take full control of your personal and team knowledge through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Mem AI (Knowledge Workspace) tools. Connect 12 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Knowledge Orchestration — Create new mems (notes) using Markdown directly from your agent, instantly transforming textual ideas into indexed knowledge vectors
- AI Semantic Search — Leverage dense semantic similarity to find notes across your entire workspace, identifying relevant information based on meaning rather than explicit keywords
- Deep Content Retrieval — Extract the full scalar text body and context metadata for specific mems to retrieve precise project details securely
- Collection Management — Establish thematic groupings (Collections) and attach live mems structurally to maintain organized project boundaries natively
- Quick Capture (Mem It) — Trigger rapid capture blocks for links, snippets, or raw thoughts, allowing your agent to log ideas without manual dashboard navigation
- Contextual Updates — Mutate existing mem content to keep project logs and meeting notes up-to-date while preserving historical knowledge mappings
- Resource Inventory — List all available mems or explore specific collections to understand your knowledge distribution and team documentation footprint
The Mem AI (Knowledge Workspace) MCP Server exposes 12 tools through the Vinkius. Connect it to AutoGen in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Mem AI (Knowledge Workspace) to AutoGen via MCP
Follow these steps to integrate the Mem AI (Knowledge Workspace) MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 12 tools from Mem AI (Knowledge Workspace) automatically
Why Use AutoGen with the Mem AI (Knowledge Workspace) MCP Server
AutoGen provides unique advantages when paired with Mem AI (Knowledge Workspace) through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Mem AI (Knowledge Workspace) tools to solve complex tasks
Role-based architecture lets you assign Mem AI (Knowledge Workspace) tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Mem AI (Knowledge Workspace) tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Mem AI (Knowledge Workspace) tool responses in an isolated environment
Mem AI (Knowledge Workspace) + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Mem AI (Knowledge Workspace) MCP Server delivers measurable value.
Collaborative analysis: one agent queries Mem AI (Knowledge Workspace) while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Mem AI (Knowledge Workspace), a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Mem AI (Knowledge Workspace) data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Mem AI (Knowledge Workspace) responses in a sandboxed execution environment
Mem AI (Knowledge Workspace) MCP Tools for AutoGen (12)
These 12 tools become available when you connect Mem AI (Knowledge Workspace) to AutoGen via MCP:
add_mem_to_collection
Attach live Mems structurally inside explicitly mapped Collections
create_collection
Establish new logical thematic groupings mapping notes
create_mem
ai. Converts plain textual knowledge to indexed vectors immediately mapped implicitly via AI. Create a new mem (note) in Mem.ai using Markdown
delete_mem
No recovery is possible via API. Irreversibly vaporize a mem document globally
get_collection
Inspect specific Collection metadata elements
get_mem
Retrieve explicit full context metadata by target Mem ID
list_collection_mems
Query ALL explicit Mem bodies inside specific Collections
list_collections
Query explicitly tracked thematic Collections arrays
list_mems
Returns identifiers and raw bodies. Careful, this returns heavy payloads. List all raw mems across the global workspace
mem_it
Quick capture shortcut generating automated blocks
search_mems
AI semantic search looking into all indexed knowledge
update_mem
Replaces absolute text values so ensure `get_mem` was run to append rather than destroy inadvertently. Update pre-existing mem content natively swapping strings
Example Prompts for Mem AI (Knowledge Workspace) in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Mem AI (Knowledge Workspace) immediately.
"Search my mems for anything related to 'quarterly business review'"
"Create a new mem with today's standup notes in Markdown"
"List all my thematic collections in Mem"
Troubleshooting Mem AI (Knowledge Workspace) MCP Server with AutoGen
Common issues when connecting Mem AI (Knowledge Workspace) to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Mem AI (Knowledge Workspace) + AutoGen FAQ
Common questions about integrating Mem AI (Knowledge Workspace) MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
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Microsoft's framework for multi-agent collaborative conversations.
Connect Mem AI (Knowledge Workspace) to AutoGen
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.